9 finite-element-method Fellowship positions at Australian National University in Australia
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Australian National University | Canberra, Australian Capital Territory | Australia | about 9 hours ago
-elliptic diffusion processes which are induced by geometric flows, with the aim of producing new and robust methods of establishing convergence results for many flow processes. The level of this appointment
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Australian National University | Canberra, Australian Capital Territory | Australia | about 9 hours ago
bring: PhD in bioinformatics, computational biology or a related field. Experience or interest in applying computational methods to RNA/mRNA therapeutics. A demonstrated ability to publish high-quality
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Australian National University | Canberra, Australian Capital Territory | Australia | about 9 hours ago
University. Located within the School of Art and Design, the Design program combines contemporary design methods and digital technologies with hands-on making. It prepares graduates who are skilled, inventive
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Australian National University | Canberra, Australian Capital Territory | Australia | about 23 hours ago
are induced by geometric flows, with the aim of producing new and robust methods of establishing convergence results for many flow processes. The level of this appointment, Academic Level A or B, will be
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Australian National University | Canberra, Australian Capital Territory | Australia | about 9 hours ago
to contribute to a broader portfolio of research and outreach projects on decarbonisation, including of heavy industry in Australia, working collaboratively with other researchers. Methods are broadly in
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independent research in molecular biology and biophysics, focusing on computational simulations to examine protein structure and function. This includes using advanced sampling methods and free
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Science and Technology. It aims to develop computational representations and methods for efficient sequential decision-making under uncertainty with applications in multi-robot domain. We will explore
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approaches to model uncertainty for learned computer vision systems, including dense prediction. The position will develop novel methods for deep learning in computer vision that accurately quantify their own
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community, check out our Twitter and Instagram . We have a reputation for international leadership and innovation, focused on developing new methods, whether experimental, analytical or computational. Our